Merge branch 'master' of skozl.com:e4-gan

1 files changed, 0 insertions, 39 deletions

diff --git a/lib/virtual_batch.py b/lib/virtual_batch.py
deleted file mode 100644
index dab0419..0000000
--- a/lib/virtual_batch.py
+++ /dev/null
@@ -1,39 +0,0 @@
-import tensorflow as tf
-from tensorflow.keras import backend as K
-from tensorflow.keras.layers import Layer
-from lib.virtual_batchnorm_impl import VBN
-from tensorflow.python.framework import tensor_shape
-from tensorflow.python.keras.engine.base_layer import InputSpec
-from tensorflow.python.keras import initializers
-
-class VirtualBatchNormalization(Layer):
-    def __init__(self,
-               momentum=0.99,
-               center=True,
-               scale=True,
-               beta_initializer='zeros',
-               gamma_initializer='ones',
-               beta_regularizer=None,
-               gamma_regularizer=None,
-               **kwargs):
-
-        self.beta_initializer = initializers.get(beta_initializer)
-        self.gamma_initializer = initializers.get(gamma_initializer)
- 
-        super(VirtualBatchNormalization, self).__init__(**kwargs)
-
-    def build(self, input_shape):
-        input_shape = tensor_shape.TensorShape(input_shape)
-        if not input_shape.ndims:
-          raise ValueError('Input has undefined rank:', input_shape)
-        ndims = len(input_shape)
-        self.input_spec = InputSpec(ndim=ndims)
-        #super(VirtualBatchNormalization, self).build(input_shape)  # Be sure to call this at the end
-
-    def call(self, x):
-        outputs = VBN(x, gamma_initializer=self.gamma_initializer, beta_initializer=self.beta_initializer)(x)
-        outputs.set_shape(x.get_shape())
-        return outputs
-
-    def compute_output_shape(self, input_shape):
-        return input_shape